We describe a new molecular approach to analyzing the genetic diversity of complex microbial populations in a parched soil.

Background

This technique is based on the separation of polymerase chain reaction-amplified fragments of genes coding for 16S rRNA

Methods

The study of microbial community structure was done using environmental DNA samples isolated directly from crude oil-polluted soil, and subsequent polymerase chain reaction (PCR) amplification of total community 16S rDNA. Evaluation of differences in the metabolic soil sample`s profiles employed Commmunity Level Physiological Profiling with the use of Biolog EcoPlate® system.

Results

Analysis of different microbial communities demonstrated the presence of up to 10 distinguishable bands in the separation pattern, which were most likely derived from as many different species constituting these populations, and thereby generated a unique profile of the populations. We showed that it is possible to identify constituents which represent only 1% of the total population. On analysis using multivariate factor, we observed correlation of consumption rates for polymer, carbohydrates, amines and amides correlates with metabolic patterns in the studied communities. Analysis of microbial diversity using Shannon H index, identified indigenous Hevea brasilensis cultivated-soil populations with the highest diversity in polluted regimes and were more resistant, maintaining a steady growth after day 1 for the 9 days of incubation study. Analysis of the genomic DNA from a bacterial biofilm grown under aerobic conditions suggests that sulfate-reducing bacteria, despite their anaerobicity, were present in this environment.

Conclusions

Different levels of disturbance have different effects on species and diversity. The results obtained demonstrate that this technique will contribute to our understanding of the genetic diversity of uncharacterized microbial populations.